The Syllabus Based Web Content Extractor (SBWCE)

Syllabus Based Web Content Extractor (SBWCE) introduces a new technique of Syllabus Based Web Content Mining. It makes the Syllabus Based Web Content Extraction easy and creates an instant online book view based on the links relevant to the given Syllabus. Three important contributions are made by the current work. First, as multiple format educational information is needed for Syllabus based content; the technique used makes the finding of such content easier. Second, a new approach for capturing and recording the heuristics involved during searching by experts is used. Third, the grouping of Syllabus Words for precise extraction is exploited. This paper introduces SBWCE and presents the related details

An Experimental Study to Identify the Impact of Expert Filter Tokens for Syllabus Based Searches

People search using search engines like Google. While specifying the query, some other words (filter tokens) are used with the topic being searched. These help in the filtering of the relevant and effective search results. SBWCE is being developed to make the Syllabus based Web Content Extraction easy and automatic. As SBWCE is based on using Expert Filter Tokens, there was a need to study their impact. Therefore, a framework to study the impact of these expert filter tokens was used on ‘Computer Organization and Assembly Language’, for experimental study. This paper presents the related details

EN-BIRTH Data Collector Training - Handbook and Manual

The EN-BIRTH study aims to validate selected newborn and maternal indicators for routine facility-based tracking of coverage and quality of care for use at district, national and global levels. The item contains the EN-BIRTH_Trainer's Manual (14 June 2017) and EN-BIRTH_Training Handbook (23 May 2017)

Multimodal Classification of Teaching Activities from University Lecture Recordings

[EN] The way of understanding online higher education has greatly changed due to the worldwide pandemic situation. Teaching is undertaken remotely, and the faculty incorporate lecture audio recordings as part of the teaching material. This new online teaching-learning setting has largely impacted university classes. While online teaching technology that enriches virtual classrooms has been abundant over the past two years, the same has not occurred in supporting students during online learning. To overcome this limitation, our aim is to work toward enabling students to easily access the piece of the lesson recording in which the teacher explains a theoretical concept, solves an exercise, or comments on organizational issues of the course. To that end, we present a multimodal classification algorithm that identifies the type of activity that is being carried out at any time of the lesson by using a transformer-based language model that exploits features from the audio file and from the automated lecture transcription. The experimental results will show that some academic activities are more easily identifiable with the audio signal while resorting to the text transcription is needed to identify others. All in all, our contribution aims to recognize the academic activities of a teacher during a lesson.This research was funded by the project CAR: Classroom Activity Recognition of GENERALITAT VALENCIANA. CONSELLERIA D'EDUCACIO grant number PROMETEO/2019/111.Sapena Vercher, O.; Onaindia De La Rivaherrera, E. (2022). Multimodal Classification of Teaching Activities from University Lecture Recordings. Applied Sciences. 12(9):1-18. https://doi.org/10.3390/app1209478511812

A Multidisciplinary Approach to the Reuse of Open Learning Resources

Educational standards are having a significant impact on e-Learning. They allow for better exchange of information among different organizations and institutions. They simplify reusing and repurposing learning materials. They give teachers the possibility of personalizing them according to the student’s background and learning speed. Thanks to these standards, off-the-shelf content can be adapted to a particular student cohort’s context and learning needs. The same course content can be presented in different languages. Overall, all the parties involved in the learning-teaching process (students, teachers and institutions) can benefit from these standards and so online education can be improved. To materialize the benefits of standards, learning resources should be structured according to these standards. Unfortunately, there is the problem that a large number of existing e-Learning materials lack the intrinsic logical structure required, and further, when they have the structure, they are not encoded as required. These problems make it virtually impossible to share these materials. This thesis addresses the following research question: How to make the best use of existing open learning resources available on the Internet by taking advantage of educational standards and specifications and thus improving content reusability?In order to answer this question, I combine different technologies, techniques and standards that make the sharing of publicly available learning resources possible in innovative ways. I developed and implemented a three-stage tool to tackle the above problem. By applying information extraction techniques and open e-Learning standards to legacy learning resources the tool has proven to improve content reusability. In so doing, it contributes to the understanding of how these technologies can be used in real scenarios and shows how online education can benefit from them. In particular, three main components were created which enable the conversion process from unstructured educational content into a standard compliant form in a systematic and automatic way. An increasing number of repositories with educational resources are available, including Wikiversity and the Massachusetts Institute of Technology OpenCourseware. Wikivesity is an open repository containing over 6,000 learning resources in several disciplines and for all age groups [1]. I used the OpenCourseWare repository to evaluate the effectiveness of my software components and ideas. The results show that it is possible to create standard compliant learning objects from the publicly available web pages, improving their searchability, interoperability and reusability

Designing web-based adaptive learning environment : distils as an example

In this study, two components are developed for the Web-based adaptive learning: an online Intelligent Tutoring Tool (ITT) and an Adaptive Lecture Guidance (ALG). The ITT provides students timely problem-solving help in a dynamic Web environment. The ALG prevents students from being disoriented when a new domain is presented using Web technology. A prototype, Distributed Intelligent Learning System (DISTILS), has been implemented in a general chemistry laboratory domain. In DISTILS, students interact with the ITT through a Web browser. When a student selects a problem, the problem is formatted and displayed in the user interface for the student to solve. On the other side, the ITT begins to solve the problem simultaneously. The student can then request help from the ITT through the interface. The ITT interacts with the student, verifying those solution activities in an ascending order of the student knowledge status. In DISTILS, a Web page is associated with a HTML Learning Model (HLM) to describe its knowledge content. The ALG extracts the HLM, collects the status of students\u27 knowledge in HLM, and presents a knowledge map illustrating where the student is, how much proficiency he/she already has and where he/she is encouraged to explore. In this way, the ALG helps students to navigate the Web-based course material, protecting them from being disoriented and giving them guidance in need. Both the ITT and ALG components are developed under a generic Common Object Request Broker Architecture (CORBA)-driven framework. Under this framework, knowledge objects model domain expertise, a student modeler assesses student\u27s knowledge progress, an instruction engine includes two tutoring components, such as the ITT and the ALG, and the CORBA-compatible middleware serves as the communication infrastructure. The advantage of such a framework is that it promotes the development of modular and reusable intelligent educational objects. In DISTILS, a collection of knowledge objects were developed under CORBA to model general chemistry laboratory domain expertise. It was shown that these objects can be easily assembled in a plug-and-play manner to produce several exercises for different laboratory experiments. Given the platform independence of CORBA, tutoring objects developed under such a framework have the potential to be easily reused in different applications. Preliminary results showed that DISTILS effectively enhanced learning in Web environment. Three high school students and twenty-two NJIT students participated in the evaluation of DISTILS. In the final quiz of seven questions, the average correct answers of the students who studied in a Web environment with DISTILS (DISTILS Group) was 5.3, and the average correct answers of those who studied in the same Web environment without DISTILS (NoDISTILS Group) was 2.75. A t-test conducted on this small sample showed that the DISTILS group students significantly scored better than the NoDISTILS group students

NLP-based personal learning assistant for school education

Computer-based knowledge and computation systems are becoming major sources of leverage for multiple industry segments. Hence, educational systems and learning processes across the world are on the cusp of a major digital transformation. This paper seeks to explore the concept of an artificial intelligence and natural language processing (NLP) based intelligent tutoring system (ITS) in the context of computer education in primary and secondary schools. One of the components of an ITS is a learning assistant, which can enable students to seek assistance as and when they need, wherever they are. As part of this research, a pilot prototype chatbot was developed, to serve as a learning assistant for the subject Scratch (Scratch is a graphical utility used to teach school children the concepts of programming). By the use of an open source natural language understanding (NLU) or NLP library, and a slackbased UI, student queries were input to the chatbot, to get the sought explanation as the answer. Through a two-stage testing process, the chatbot’s NLP extraction and information retrieval performance were evaluated. The testing results showed that the ontology modelling for such a learning assistant was done relatively accurately, and shows its potential to be pursued as a cloud-based solution in future

An Investigation of Language Teachers’ Explorations of the Use of Corpus Tools in the English for Academic Purposes (EAP) Class

Despite claims that the use of corpus tools can have a major impact in language classrooms (e.g., Conrad, 2000, 2004; Davies, 2004; O\u27Keefe, McCarthy, & Carter, 2007; Sinclair, 2004b; Tsui, 2004), many language teachers express apparent apathy or even resistance towards adding corpus tools to their repertoire (Cortes, 2013b). This study examines from a teacher cognition perspective (Borg, 2006) how three EAP (English for Academic Purposes) writing teachers identified their most pressing needs and considered possible ways that corpus tools might address those needs. After having an individualized corpus working session, each teacher put into practice one or more corpus tools to address self-identified needs in their writing classes. The teachers reflected on the process across a series of interviews and in a stimulated recall session, which were analyzed using qualitative research methods. Each teacher discussed the degree to which the lesson met her objectives, and considered how she might use such corpus tools in the future, as one component in the development of her teaching beliefs, knowledge base, and practices. Through thematic analysis of the interviews and the individualized corpus working sessions, themes emerged that tell the story of these three teachers as they moved through this process, relating to the issues of time, student engagement, material analysis, selection and design, issues related to corpus tools, language, institutional factors, and collaboration. A new area of specialization on the pedagogical uses of corpus tools is discussed, based on the results of the three cases. Implications for researchers, material designers, corpus tools specialists, teacher educators, administrators and teachers are considered